Mcpproxy Go

📺 Watch the full walkthrough  ·  📚 Read the docs  ·  🌐 mcpproxy.app

The demo above shows the embedded web UI. The MCPProxy core is a single binary for macOS, Linux, and Windows — the web UI ships inside it, with no extra service to run. On macOS, an optional menu‑bar app adds one‑click convenience (start/stop, server health, quarantine, logs).

    

macOS menu‑bar app   ·   Activity log & audit in the macOS app

Why MCPProxy?

• Scale beyond API limits – Federate hundreds of MCP servers while bypassing Cursor's 40-tool limit and OpenAI's 128-function cap.
• Spend less context on tool definitions – Agents see a small set of MCPProxy discovery and execution tools (retrieve_tools, describe_tool, the call_tool_* variants and a few management tools) instead of the full upstream tool catalog, and fetch schemas on demand (in retrieve_tools and code_execution routing; direct routing exposes upstream tools individually, see Routing modes). How much context this saves depends on the number of tools, the routing mode, the client and the task; see Token savings: what is and is not measured.
• Review before use – New servers are quarantined and their tools are withheld from agents until you review and approve them, and, under the default manual trust mode, most later changes to an approved tool's definition are held for review again. Known exceptions: input-schema-only edits outside scan mode, a newly added output schema, and a description added to a tool that was approved with an empty description are admitted without a hold; scan mode admits clean changes and misses what its detectors miss; auto mode does not hold changes. This reduces exposure to malicious tool definitions (Tool Poisoning Attacks); it is not a guarantee of safety. See What quarantine does and does not cover.
• Pluggable security scanners – Run Snyk, Semgrep, Trivy, Cisco, and other Docker-based scanners against quarantined servers before you approve them; findings are normalized to SARIF with a composite risk score. See Security scanner plugins.
• Works offline & cross-platform – A single core binary for macOS (Intel & Apple Silicon), Windows (x64 & ARM64), and Linux (x64 & ARM64), with the web UI embedded. macOS additionally ships an optional menu-bar app.

Token savings: what is and is not measured

On-demand discovery reduces how many upstream tool definitions an agent loads into context up front. The saving is not a fixed percentage: it grows with the number of connected tools and depends on the routing mode, the client and the task. MCPProxy does not publish a headline token-reduction or accuracy-improvement figure, and it makes no latency claim.

What the repository does measure, as a first-party, deterministic estimate (see bench/README.md for the method and to reproduce it with go run ./bench/cmd/bench):